Estimation in Partial Functional Linear Spatial Autoregressive Model

Yuping Hu, Siyu Wu, Sanying Feng and Junliang Jin
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Yuping Hu: School of Mathematics and Statistics, Zhengzhou University, Zhengzhou 450001, China
Siyu Wu: School of Mathematics and Statistics, Zhengzhou University, Zhengzhou 450001, China
Sanying Feng: School of Mathematics and Statistics, Zhengzhou University, Zhengzhou 450001, China
Junliang Jin: School of Mathematics and Statistics, Zhengzhou University, Zhengzhou 450001, China

Mathematics, 2020, vol. 8, issue 10, 1-12

Abstract: Functional regression allows for a scalar response to be dependent on a functional predictor; however, not much work has been done when response variables are dependence spatial variables. In this paper, we introduce a new partial functional linear spatial autoregressive model which explores the relationship between a scalar dependence spatial response variable and explanatory variables containing both multiple real-valued scalar variables and a function-valued random variable. By means of functional principal components analysis and the instrumental variable estimation method, we obtain the estimators of the parametric component and slope function of the model. Under some regularity conditions, we establish the asymptotic normality for the parametric component and the convergence rate for slope function. At last, we illustrate the finite sample performance of our proposed methods with some simulation studies.

Keywords: partial functional linear spatial autoregressive model; spatial autoregression; functional principal component analysis; instrument variable (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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